1. Field of the Invention
The present invention relates to using functional electrical stimulation to artificially activate muscle movement. More specifically, the present invention relates to a method and apparatus for activating a muscle to produce a non-isometric functional movement in a body part through functional electrical stimulation.
2. Related Art
Functional electrical stimulation (FES) of skeletal muscles can restore functional movements, such as standing or walking in patients with upper motor neuron lesions. This is achieved by applying the FES to paralyzed or weak muscles in the patients to artificially activate the functional movements.
Unfortunately, despite many technical advances, the FES has not had desirable impact on rehabilitation. This lack of effectiveness in practice is caused by several factors. Firstly, the physiological and biomechanical processes involved in the generation of FES-elicited movements are highly non-linear and time varying. Hence, numerous tests would be required to find the desired stimulation patterns necessary to produce the desired muscle force and limb motion for each patient and for each functional movement. Secondly, commercially available FES systems are typically open-loop systems which make controlling the movements of paralyzed limbs in patients extremely difficult. Finally, other factors that occur during a FES-elicited movement, such as muscle fatigue, spasticity, and the influence of voluntary upper-body forces further complicate the control task.
One solution that can partially overcome the above-described shortcomings is the use of mathematical muscle models in conjunction with FES systems that monitor muscle performance. Mathematical models that are accurate and predictive enable FES stimulators to deliver patterns customized for each person to perform a desired functional movement while continuously adapting the stimulation protocols to the actual needs of the patient.
Previously, phenomenological Hill-type, Huxley-type cross-bridge, or analytical approaches have been developed to model the behavior of muscle contraction under both isometric and non-isometric conditions. Unfortunately, all of the above mathematical models that have been developed to date have one or all of the following drawbacks: (1) they are applicable only to isometric conditions—it is desirable to extend the models to predict non-isometric contractions when the limbs are allowed to move freely in response to the FES; (2) they are only able to predict muscle forces and associated movements in response to a narrow range of stimulation frequencies—it is desirable to develop models that are able to predict muscle forces and movements to a wide range of stimulation patterns and physiological conditions; and (3) too many model parameters need to be identified, which makes the real-time implementation of the FES-based system impossible—it is desirable to minimize the number of model parameters and still be able to capture the behavior of the muscle in response to the FES.
Hence, what is needed is a method and an apparatus that uses a mathematical model which is capable of predicting a desired FES to activate a muscle to produce a desired non-isometric movement without the above-described problems.